Aims: The aim of this observational, descriptive study is to evaluate the impact of an intensive, evidence-based preventive cardiology programme on medical and lifestyle risk factors in patients at high risk of developing cardiovascular disease (CVD).
Methods: Increased CVD risk patients and their family members/partners were invited to attend a 16-week programme consisting of a professional multidisciplinary lifestyle intervention, with appropriate risk factor and therapeutic management in a community setting. Smoking, dietary habits, physical activity levels, waist circumference and body mass index, and medical risk factors were measured at initial assessment, at end of programme, and at 1-year follow up.
Results: Adherence to the programme was high, with 375 (87.2%) participants and 181 (84.6%) partners having completed the programme, with 1-year data being obtained from 235 (93.6%) patients and 107 (90.7%) partners. There were statistically significant improvements in both lifestyle (body mass index, waist circumference, physical activity, Mediterranean diet score, fish, fruit, and vegetable consumption, smoking cessation rates), psychosocial (anxiety and depression scales and quality of life indices), and medical risk factors (blood pressure, lipid and glycaemic targets) between baseline and end of programme, with these improvements being sustained at 1-year follow up.
Conclusions: These findings demonstrate how a holistic model of CVD prevention can improve cardiovascular risk factors by achieving healthier lifestyles and optimal medical management.
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http://dx.doi.org/10.1177/2047487313498831 | DOI Listing |
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
Department of Ophthalmology, China Medical University Hospital, China Medical University, Taichung, Taiwan.
To investigate for the risk of uveitis among such patients. A retrospective cohort study utilized the TriNetX database and recruited pediatric autoimmune patients diagnosed between January 1st 2004 and December 31st 2022. The non-autoimmune cohort were randomly selected control patients matched by sex, age, and index year.
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December 2024
State Key Laboratory of Frigid Zone Cardiovascular Disease, Cardiovascular Research Institute, Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, 110016, China.
The triglyceride to high density lipoprotein cholesterol (TG/HDL-C) ratio has been consistently linked with the risk of coronary heart disease (CHD). Nevertheless, there is a paucity of studies focusing on acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) or experiencing bleeding events. The study encompassed 17,643 ACS participants who underwent PCI.
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December 2024
Department of Medical and Surgical Sciences, Institute of Cardiology, University of Bologna, Policlinico S.Orsola-Malpighi, via Massarenti 9, Bologna, 40138, Italy.
Cardiac implantable electronic devices infections (CIEDI) are associated with poor survival despite the improvement in transvenous lead extraction (TLE). Aetiology and systemic involvement are driving factors of clinical outcomes. The aim of this study was to explore their contribute on overall mortality.
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